September 2010

The book starts off with the story of Ed Thorp, the father of stat arb. Priceton / Newport partners is a fund that is well known in the quant world that has a great track record of beating the market for decades and the quant behind it is Ed Thorp. If you want to read the entire story with bells and whistles about Ed Thorp, Fortune’s formula is a better book. This book though quickly summarizes the success story of Thorpe-Shannon combination and goes on to tell a nice story of four quants who strike it big in the hedge fund world. The author traces the lives of Peter Muller(Morgan Stanley PDT) , Ken Griffin( Citadel), Cliff Asness (AQR) and Boaz Weinstein(Saba) from their childhood, to their trading careers, their eccentricities, their hiring decisions , their winning and losing trades. Besides these four quants, there are host of people / funds mentioned in the book

Medallion’s fund performance is something that is revered by every one at Wall Street . 40% returns for three decades is god level performance in the quant fund space. Author traces the story of the fund from the inception to its performance over the years. Renaissance is always considered a mysterious place for many reasons. They hire scientists from fields like Voice Recognition space, Crypto analysis etc. Like google, they have 40 hours dedicated to research time that has no restrictions. I have never heard of any quant fund that has this policy of “unstructured time” until I read this book. In all likelihood all their breakthrough work might be a result of this “unstructured time” of all 90 odd Phds in the company. One of my professors used to say that there are dedicated Phds at Medallion who focus just on “Data Missing Treatment analysis”. They write tons of algos to treat the missing data.Obviously very little is known about this fund and one can only read between the lines of the statements in the press that , as a fund, they believe that asset values follow CLOSE to random walk(not a complete random walk) and it is their endeavour to get that little edge out of understanding it and subsequently using that understanding to spread it across multiple bets. If ever Jim Simons retires and decides to write a book about his fund , I guess it will be a fascinating read! . Till then like a Hidden Markov Model, one can only form mental models of what they are up to 🙂

Chapter 10 of the book titled “August Factor”, is what I liked the most. It gives a hollywodesque spin to the Liquidity squeeze that happened in the week of Aug 6 2007. Khandani and Lo have written a superb analysis on the same. However author narrates it in a story format sans the numbers and the math. You forget for a moment that you are reading a book about finance and you are pulled in to a thriller ride, a ride , though , which cost the quant funds millions of dollars. Aaron Brown feels that quant community will remember Aug 07 more than the subprime crisis as the week showed that all models can go wrong. Every Quant fund on the street lost money because of massive deleveraging and Short Squeeze.

A recount of the Lehmann’s fall, AIG’s bailout is given in the context of Andrew Lo’s Doomsday clock. Lo and Khandani wrote an insightful article analyzing the liquidity crisis in Aug 07 and talked about the hedge fund industry and the doomsday clock. Here is in essence what they are saying :

In the aftermath of the Second World War, a group of socially minded physicists joined to form the Bulletin of Atomic Scientists to raise public awareness of the potential for nuclear holocaust. To illustrate their current assessment of the appropriate state of alarm, they published a “Doomsday Clock” indicating how close we are to “midnight”, i.e., nuclear annihilation. Originally set at 7 minutes to midnight in 1947, the clock has changed from time to time as we have moved closer to (2 minutes to midnight in 1953) or farther from (17 minutes to midnight in 1993) the brink of nuclear disaster. If we were to develop a Doomsday Clock for the hedge-fund industry’s impact on the global nancial system, calibrated to 5 minutes to midnight in August 1998, and 15 minutes to midnight in January 1999, then our current outlook for the state of systemic risk in the hedge-fund industry is about 11:51pm.

Despite the warning, Crisis happened!

The author cites Derman, Thorpe , Wilmott , Mandelbrot, Taleb to make a point that “ We are modeling humans and not machines” and hence takes a dig at the quasi-physics approach taken for quant modeling. Despite, the warnings from Mandelbrot, Wilmott and others much before the crisis, the faulty models were rampant. Why ? There is no single answer for it. The following manifesto was in circulation well before the crisis, but it did not stop quants from using faulty models!

The Modelers’ Hippocratic Oath

I will remember that I didn’t make the world, and it doesn’t satisfy my equations.

Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.

I will never sacrifice reality for elegance without explaining why I have done so.

Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.

I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.

The book talks about the performance of AQR(Cliff Asness) ,Citadel( Ken Griffin) and Saba(Boaz Weinstein) during the crisis and hints at the black swan effect on any fund’s performance. Citadel has never lost money except for 1995 in its two decades of existence and in 2008 , it was on the verge of collapse in just one year. AQR lost half its war chest ($20B) in 2008 betting on value centric models, treasuries, currencies, real estate etc. Saba which controlled $30 B was shut down post crisis. The damage is really mind-blowing stuff. By providing the gory details of the crisis , you can’t help but notice that the most dangerous word in QUANT’s career is “UNPRECEDENTED”. If there are regimes when historical data and patterns are not an indicator of the way things function, then basically a quant should be completely ignored.

So, who did well and survived the crisis. Renaissance for one was top notch in performance.Medallion’s fund gained 80% in 2008 ! It’s a jaw dropping number if you think of the panic and investors behaviour in the market. In Jim Simons words

Our approach is driven by my background as a mathematician. We manage funds whose trading is determined by mathematical formulas….We operate only in highly liquid publicly traded securities, meaning we don’t trade in credit default swaps or CDOs. Our trading models tend to be contrarian , buying stocks recently out of favor and selling those recently in favor.

Renaissance was also free of the theoretical baggage of modern portfolio theory or EMH/CAPM. Rather the fund was run like a machine, a scientific experiment and the only thing that mattered was whether a strategy worked or not – whether it made money. In the end, THE TRUTH wasn’t whether the market was efficient or in equilibrium. THE TRUTH was very simple, and remorseless as he driving force of any Wall Street Banker, “ Did you make money or not ? Nothing else mattered

Fund floated by Black swan’s Taleb , Universa investments itself became a black swan as the AUM increased from $300M in Jan 07, to $6B by Mid 2009. High frequency trading outfits did exceptionally well. High frequency outfits made a lot of money like Tactical trading (arm of Citadel).

Somehow reading about the people who made/lost money makes me think that, one must rely on math and non-parametric assumption free statistics than finance theory laden models. When I hear the word factor models from any person pitching his model, the one thing that flashes in my mind is “ The ton of assumptions that factor models make” and I start wondering , Are they really valid ?, If you have back tested and it works for x years, will it work next year ? Who decides factors ? For a handful of assets, the covariance matrix might be stable but when you taking the entire market of securities which pass some market cap filter or liquidity filter, are the covariance matrices stable ? have you taken fat tails distributions in your model ?..The more I think of it, the more I realize that factor models are a CONVENIENT form of summarizing the market returns. But CONVENIENCE need not equate to CASH FLOW.

The book ends with a note on dark pools, an off-regulatory limit exchange which almost every fund manager uses it in US. Quite contrary to the title of the book which hints to a casual onlooker that, Quant is on a decline, the book ends with this statement

It leaves an indelible impression on the readers mind that , whether one believes or not, Quant is a reality in the market place and all exchanges are morphing in to giant supercomputers. Here is a under-construction pic of the NYSE data centre at Mahwah, New Jersey.

NYSE Data Centre Mahwah, NJ

The Facility is as BIG as 7 FOOTBALL Fields

Whatever be the opinions floating around quant, HighFreq Trading , mediocristan / extremistan , fat tails, distribution free models……, one thing looks certain….We are going to see money making machines AND massive blowups at a much smaller time scale. The next LTCM / Paulson & Co type fund would lose or make tons of money , may be in just 5 minutes!